AI-native customer support,
purpose-built for India's
loan service providers.
Lokta unifies multi-lender support, lending-aware classification, and compliance-grade AI in a single workbench — so your agents resolve faster, your borrowers self-serve in their language, and every interaction leaves an RBI-ready audit trail.
- Multi lender from day one
- 40+ lending-specific intents
- <1s sync triage
- RBI-ready audit by default
Servicing loans across multiple lenders is its own discipline.
Generic helpdesks weren't designed for this. Generic AI doesn't understand your policies. Building it in-house pulls engineering away from origination.
- Tribal knowledge trapped in tenured agents
- Tickets sprawl across WhatsApp, email, phone, portal, Slack
- Compliance teams chase evidence you can't assemble
- Generic helpdesks ignore your partner taxonomy
- In-house builds pull engineering from origination
- Tenant-isolated by client_id — every record, every log
- One workbench for every partner channel
- Audit trail captured on every interaction
- Lending-aware triage out of the box
- Ship the playbook, not the platform
Lokta is different. It's lending-native, multi-partner from day one, and engineered around the way LSPs actually operate.
New to the terminology? LOS vs LMS vs LSP sets out how an LSP differs from the origination and servicing systems it runs on.
Why LSPs choose Lokta.
Multi-partner from the core
Tenant isolation by client_id runs through every record — cases, messages, knowledge, audit logs, dashboards. Add a new partner without changing code.
Lending-native intelligence
Triage understands KYC, disbursement, repayment, NACH/ECS, foreclosure, hardship, settlement — and what those look like at each lifecycle stage. Not retrofitted from generic CX.
Compliance-first AI
Every AI decision is logged with confidence, tools used, and human override. PII is masked. Verbatim templates can't be rewritten by an LLM. Humans approve before borrowers see the response.
Six capabilities engineered for multi-partner servicing.
Partner-aware pre-triage
Inbound emails route to the right partner deterministically — before any AI runs. Borrower phone numbers and IDs resolve the rest. Your agents see only their partner's queue.
Three-level classification, lending taxonomy
Tag 1 (partner + journey stage) → Subtag 1 (issue category) → Subtag 2 (intent). 40+ lending-specific intents, classified synchronously in under a second. Routing decisions happen at intake, not after.
MCP-first integrations
One MCP server per LMS, LOS, bureau, or partner system. Plug in your LMS, LOS, bureau, or CRM without writing custom connectors. The same MCPs can power your customer-facing chatbot and your support agent's tools.
Multilingual borrower self-service
WhatsApp, email, and portal bots that detect Hindi, Hinglish, English, and major regional languages — and respond in kind. Foreclosure quotes, statement requests, payment troubleshooting, NACH status — handled before a human is needed.
Per-partner SOPs and ground rules
A unified knowledge base scoped by partner, product, and lifecycle stage. Verbatim-tagged compliance templates the AI can reference but never rewrite. The system flags KB gaps from real ticket volume so your SOPs evolve with your operation.
Configurable autonomy per channel
Shadow (AI logs only) → Copilot (AI drafts, human sends) → Selective Automation (AI sends when confidence clears your threshold). Toggle per channel, per partner. Loosen as you build trust.
From channel to closed ticket — without tab-switching.
- 01Day 0Setup
Connect your inbound channels. Map your partners' email domains. Wire your LMS via MCP. Import your FAQs — the AI starts learning from real tickets immediately.
- 02Daily opsRun
Borrower writes in → resolved to the right partner → classified by lifecycle stage and intent → loan and borrower context auto-attached → agent sees a draft reply with confidence score and the SOPs it cited → reviews → sends.
- 03ContinuousLearn
The Knowledge Harvester surfaces SOP gaps from your unanswered tickets. Analytics segment by partner, channel, intent, and SLA — without mixing data across lenders.
Built around RBI's Digital Lending Guidelines.
Every AI interaction is logged, reviewable, and explainable — designed for RBI-regulated servicing environments.
08:42:14.221 AUDIT ✓ Every model call, tool use, data access, and human override logged.
08:42:14.224 PII-MASK ✓ Aadhaar, PAN, IFSC, bank account, mobile, email — masked at ingest.
08:42:14.226 GUARDRAIL ✓ Prompt-injection / jailbreak attempt blocked before reaching agents.
08:42:14.231 TEMPLATE ✓ Verbatim / locked compliance text — AI can reference, never paraphrase.
08:42:14.234 HUMAN-GATE ✓ Confidence below threshold — held for human approval.Even five years from now, we won't trust AI 100%. The conversation is always visible.
— Lokta product principle
Questions LSPs ask before the demo.
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How does Lokta isolate data between my partner lenders?
Tenant isolation by client_id runs through every record — cases, messages, knowledge base, audit logs, dashboards, and analytics. An agent assigned to Partner A only sees Partner A's queue; the AI's retrieval is scoped to Partner A's SOPs and verbatim templates; analytics never mix volumes across lenders. New partners are added through configuration, not code, so each onboarding is a setup task rather than a release.
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What does 'lending-native classification' actually mean?
Triage understands the entities and lifecycle stages specific to lending — KYC, disbursement, repayment, NACH/ECS, foreclosure, hardship, settlement — and what each issue looks like at each stage of the loan. Tag 1 (partner + journey stage) → Subtag 1 (issue category) → Subtag 2 (intent), resolved at ingest in under a second across 40+ lending-specific intents. Generic CX tools start with retail categories and bolt lending on; Lokta starts at the LMS.
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How does Lokta stay RBI-compliant?
Every AI interaction is logged with confidence score, tools used, retrieved evidence, and human override — designed to satisfy RBI Digital Lending Guidelines reviewability. PII (Aadhaar, PAN, IFSC, bank account, mobile, email) is masked at ingest before reaching any model. Verbatim compliance templates can be cited by the AI but never paraphrased. Confidence below the configured threshold holds the response for human approval before the borrower sees it.
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Do I need to replace my LMS to use Lokta?
No. Lokta integrates with your existing LMS, LOS, bureau, and partner systems via MCP servers — one MCP per system — without writing custom connectors. The same MCPs that power agent tools can power your customer-facing chatbot. You can run Lokta's servicing agent alongside Lokta's loan-management core if you want the full connected stack, or stand-alone on top of whatever your partners run today.
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How autonomous is the AI, and can I dial it back?
Three modes per channel, per partner: shadow (AI logs draft responses but humans send), copilot (AI drafts, human reviews and sends), and selective automation (AI sends when confidence clears your threshold). Most LSPs start in shadow on a new partner, move to copilot once accuracy is stable, and graduate channel-by-channel to selective automation as trust builds. You can dial it back at any time, per channel, per partner — without redeploying.
See Lokta on your own ticket data.
30-minute demo. We'll triage a real sample of your tickets, show partner-aware routing live, and walk through how your team would use the workbench.